Identification and classification of spine vertebrae by automated methods

We are currently working toward developing computer-assisted methods for the indexing of a collection of 17,000 digitized x-ray images by biomedical content. These images were collected as part of a nationwide health survey and form a research resource for osteoarthitis and bone morphometry. This task requires the development of algorithms to robustly analyze the x-ray contents for key landmarks, to segment the vertebral bodies, to accurately measure geometric features of the individual vertebrae and inter-vertebral areas, and to classify the spine anatomy into normal or abnormal classes for conditions of interest, including anterior osteophytes and disc space narrowing. Subtasks of this work have been created and divided among collaborators. In this paper, we provide a technical description of the overall task, report on progress made by collaborators, and provide the most recent results of our own research into obtaining first-order location of the spine region of interest by automated methods. We are currently concentrating on images of the cervical spine, but will expand the work to include the lumbar spine as well. Development of successful image processing techniques for computer-assisted indexing of medical image collections is expected to have a significant impact within the medical research and patient care systems.